






'''simple docstring'''





import collections
import os
import re
from pathlib import Path


_UpperCamelCase						:						Optional[int]  =					'src/transformers'


# Matches is_xxx_available()
_UpperCamelCase						:						int  =					re.compile(R'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
_UpperCamelCase						:						Dict  =					re.compile(R'^_import_structure\s+=\s+\{([^\}]+)\}')
# Catches a line with a key-values pattern: "bla": ["foo", "bar"]
_UpperCamelCase						:						List[str]  =					re.compile(R'\s+"\S*":\s+\[([^\]]*)\]')
# Catches a line if not is_foo_available
_UpperCamelCase						:						Any  =					re.compile(R'^\s*if\s+not\s+is\_[a-z_]*\_available\(\)')
# Catches a line _import_struct["bla"].append("foo")
_UpperCamelCase						:						Dict  =					re.compile(R'^\s*_import_structure\["\S*"\]\.append\("(\S*)"\)')
# Catches a line _import_struct["bla"].extend(["foo", "bar"]) or _import_struct["bla"] = ["foo", "bar"]
_UpperCamelCase						:						Tuple  =					re.compile(R'^\s*_import_structure\[\S*\](?:\.extend\(|\s*=\s+)\[([^\]]*)\]')
# Catches a line with an object between quotes and a comma:     "MyModel",
_UpperCamelCase						:						Union[str, Any]  =					re.compile(R'^\s+"([^"]+)",')
# Catches a line with objects between brackets only:    ["foo", "bar"],
_UpperCamelCase						:						str  =					re.compile(R'^\s+\[([^\]]+)\]')
# Catches a line with from foo import bar, bla, boo
_UpperCamelCase						:						Union[str, Any]  =					re.compile(R'\s+from\s+\S*\s+import\s+([^\(\s].*)\n')
# Catches a line with try:
_UpperCamelCase						:						Optional[int]  =					re.compile(R'^\s*try:')
# Catches a line with else:
_UpperCamelCase						:						List[Any]  =					re.compile(R'^\s*else:')
def __UpperCAmelCase   (					A					:			Any		)    ->   Tuple:
			if _re_test_backend.search(A		) is None:
						return None
			UpperCAmelCase_      :       str          =       [b[0] for b in _re_backend.findall(A		)]
			backends.sort()
			return "_and_".join(A		)
def __UpperCAmelCase   (					A					:			List[Any]		)    ->   Optional[int]:
			with open(A			,       '''r'''			,       encoding='''utf-8'''			,       newline='''\n'''		) as f:
						UpperCAmelCase_      :       str          =       f.readlines()

			UpperCAmelCase_      :       List[str]          =       0
			while line_index < len(A		) and not lines[line_index].startswith('''_import_structure = {'''		):
						line_index += 1

			# If this is a traditional init, just return.
			if line_index >= len(A		):
						return None

			# First grab the objects without a specific backend in _import_structure
			UpperCAmelCase_      :       Tuple          =       []
			while not lines[line_index].startswith('''if TYPE_CHECKING'''		) and find_backend(lines[line_index]		) is None:
						UpperCAmelCase_      :       List[Any]          =       lines[line_index]
						# If we have everything on a single line, let's deal with it.
						if _re_one_line_import_struct.search(A		):
									UpperCAmelCase_      :       str          =       _re_one_line_import_struct.search(A		).groups()[0]
									UpperCAmelCase_      :       Any          =       re.findall(r'''\[([^\]]+)\]'''			,       A		)
									for imp in imports:
												objects.extend([obj[1:-1] for obj in imp.split(''', '''		)]		)
									line_index += 1
									continue
						UpperCAmelCase_      :       Dict          =       _re_import_struct_key_value.search(A		)
						if single_line_import_search is not None:
									UpperCAmelCase_      :       List[str]          =       [obj[1:-1] for obj in single_line_import_search.groups()[0].split(''', '''		) if len(A		) > 0]
									objects.extend(A		)
						elif line.startswith(''' ''' * 8 + '''"'''		):
									objects.append(line[9:-3]		)
						line_index += 1

			UpperCAmelCase_      :       int          =       {'''none''': objects}
			# Let's continue with backend-specific objects in _import_structure
			while not lines[line_index].startswith('''if TYPE_CHECKING'''		):
						# If the line is an if not is_backend_available, we grab all objects associated.
						UpperCAmelCase_      :       Any          =       find_backend(lines[line_index]		)
						# Check if the backend declaration is inside a try block:
						if _re_try.search(lines[line_index - 1]		) is None:
									UpperCAmelCase_      :       int          =       None

						if backend is not None:
									line_index += 1

									# Scroll until we hit the else block of try-except-else
									while _re_else.search(lines[line_index]		) is None:
												line_index += 1

									line_index += 1

									UpperCAmelCase_      :       str          =       []
									# Until we unindent, add backend objects to the list
									while len(lines[line_index]		) <= 1 or lines[line_index].startswith(''' ''' * 4		):
												UpperCAmelCase_      :       Optional[Any]          =       lines[line_index]
												if _re_import_struct_add_one.search(A		) is not None:
															objects.append(_re_import_struct_add_one.search(A		).groups()[0]		)
												elif _re_import_struct_add_many.search(A		) is not None:
															UpperCAmelCase_      :       Dict          =       _re_import_struct_add_many.search(A		).groups()[0].split(''', '''		)
															UpperCAmelCase_      :       Dict          =       [obj[1:-1] for obj in imports if len(A		) > 0]
															objects.extend(A		)
												elif _re_between_brackets.search(A		) is not None:
															UpperCAmelCase_      :       int          =       _re_between_brackets.search(A		).groups()[0].split(''', '''		)
															UpperCAmelCase_      :       List[Any]          =       [obj[1:-1] for obj in imports if len(A		) > 0]
															objects.extend(A		)
												elif _re_quote_object.search(A		) is not None:
															objects.append(_re_quote_object.search(A		).groups()[0]		)
												elif line.startswith(''' ''' * 8 + '''"'''		):
															objects.append(line[9:-3]		)
												elif line.startswith(''' ''' * 1_2 + '''"'''		):
															objects.append(line[1_3:-3]		)
												line_index += 1

									UpperCAmelCase_      :       int          =       objects
						else:
									line_index += 1

    # At this stage we are in the TYPE_CHECKING part, first grab the objects without a specific backend
			UpperCAmelCase_      :       Union[str, Any]          =       []
			while (
			    line_index < len(A		)
			    and find_backend(lines[line_index]		) is None
			    and not lines[line_index].startswith('''else'''		)
			):
						UpperCAmelCase_      :       int          =       lines[line_index]
						UpperCAmelCase_      :       int          =       _re_import.search(A		)
						if single_line_import_search is not None:
									objects.extend(single_line_import_search.groups()[0].split(''', '''		)		)
						elif line.startswith(''' ''' * 8		):
									objects.append(line[8:-2]		)
						line_index += 1

			UpperCAmelCase_      :       int          =       {'''none''': objects}
			# Let's continue with backend-specific objects
			while line_index < len(A		):
						# If the line is an if is_backend_available, we grab all objects associated.
						UpperCAmelCase_      :       Optional[int]          =       find_backend(lines[line_index]		)
						# Check if the backend declaration is inside a try block:
						if _re_try.search(lines[line_index - 1]		) is None:
									UpperCAmelCase_      :       Optional[int]          =       None

						if backend is not None:
									line_index += 1

									# Scroll until we hit the else block of try-except-else
									while _re_else.search(lines[line_index]		) is None:
												line_index += 1

									line_index += 1

									UpperCAmelCase_      :       str          =       []
									# Until we unindent, add backend objects to the list
									while len(lines[line_index]		) <= 1 or lines[line_index].startswith(''' ''' * 8		):
												UpperCAmelCase_      :       Tuple          =       lines[line_index]
												UpperCAmelCase_      :       Tuple          =       _re_import.search(A		)
												if single_line_import_search is not None:
															objects.extend(single_line_import_search.groups()[0].split(''', '''		)		)
												elif line.startswith(''' ''' * 1_2		):
															objects.append(line[1_2:-2]		)
												line_index += 1

									UpperCAmelCase_      :       Optional[Any]          =       objects
						else:
									line_index += 1

			return import_dict_objects, type_hint_objects
def __UpperCAmelCase   (					A					:			Dict			,       A					:			Union[str, Any]		)    ->   Optional[Any]:

			def find_duplicates(A					:			Optional[int]		):
						return [k for k, v in collections.Counter(A		).items() if v > 1]

			if list(import_dict_objects.keys()		) != list(type_hint_objects.keys()		):
						return ["Both sides of the init do not have the same backends!"]

			UpperCAmelCase_      :       str          =       []
			for key in import_dict_objects.keys():
						UpperCAmelCase_      :       Union[str, Any]          =       find_duplicates(import_dict_objects[key]		)
						if duplicate_imports:
									errors.append(F"Duplicate _import_structure definitions for: {duplicate_imports}"		)
						UpperCAmelCase_      :       Optional[int]          =       find_duplicates(type_hint_objects[key]		)
						if duplicate_type_hints:
									errors.append(F"Duplicate TYPE_CHECKING objects for: {duplicate_type_hints}"		)

						if sorted(set(import_dict_objects[key]		)		) != sorted(set(type_hint_objects[key]		)		):
									UpperCAmelCase_      :       Optional[int]          =       '''base imports''' if key == '''none''' else F"{key} backend"
									errors.append(F"Differences for {name}:"		)
									for a in type_hint_objects[key]:
												if a not in import_dict_objects[key]:
															errors.append(F"  {a} in TYPE_HINT but not in _import_structure."		)
									for a in import_dict_objects[key]:
												if a not in type_hint_objects[key]:
															errors.append(F"  {a} in _import_structure but not in TYPE_HINT."		)
			return errors
def __UpperCAmelCase   (					)    ->   Union[str, Any]:
			UpperCAmelCase_      :       Tuple          =       []
			for root, _, files in os.walk(A		):
						if "__init__.py" in files:
									UpperCAmelCase_      :       List[Any]          =       os.path.join(A			,       '''__init__.py'''		)
									UpperCAmelCase_      :       str          =       parse_init(A		)
									if objects is not None:
												UpperCAmelCase_      :       List[str]          =       analyze_results(*A		)
												if len(A		) > 0:
															UpperCAmelCase_      :       Optional[Any]          =       F"Problem in {fname}, both halves do not define the same objects.\n{errors[0]}"
															failures.append('''\n'''.join(A		)		)
			if len(A		) > 0:
						raise ValueError('''\n\n'''.join(A		)		)
def __UpperCAmelCase   (					)    ->   str:
			UpperCAmelCase_      :       Any          =       []
			for path, directories, files in os.walk(A		):
						for folder in directories:
									# Ignore private modules
									if folder.startswith('''_'''		):
												directories.remove(A		)
												continue
									# Ignore leftovers from branches (empty folders apart from pycache)
									if len(list((Path(A		) / folder).glob('''*.py'''		)		)		) == 0:
												continue
									UpperCAmelCase_      :       Union[str, Any]          =       str((Path(A		) / folder).relative_to(A		)		)
									UpperCAmelCase_      :       List[Any]          =       short_path.replace(os.path.sep			,       '''.'''		)
									submodules.append(A		)
						for fname in files:
									if fname == "__init__.py":
												continue
									UpperCAmelCase_      :       Optional[Any]          =       str((Path(A		) / fname).relative_to(A		)		)
									UpperCAmelCase_      :       Union[str, Any]          =       short_path.replace('''.py'''			,       ''''''		).replace(os.path.sep			,       '''.'''		)
									if len(submodule.split('''.'''		)		) == 1:
												submodules.append(A		)
			return submodules


_UpperCamelCase						:						List[Any]  =					[
    'convert_pytorch_checkpoint_to_tf2',
    'modeling_flax_pytorch_utils',
    'models.esm.openfold_utils',
]
def __UpperCAmelCase   (					)    ->   int:
			# This is to make sure the transformers module imported is the one in the repo.
			from transformers.utils import direct_transformers_import

			UpperCAmelCase_      :       Dict          =       direct_transformers_import(A		)

			UpperCAmelCase_      :       List[str]          =       set(transformers._import_structure.keys()		)
			# This contains all the base keys of the _import_structure object defined in the init, but if the user is missing
			# some optional dependencies, they may not have all of them. Thus we read the init to read all additions and
			# (potentiall re-) add them.
			with open(os.path.join(A			,       '''__init__.py'''		)			,       '''r'''		) as f:
						UpperCAmelCase_      :       Dict          =       f.read()
			import_structure_keys.update(set(re.findall(r'''import_structure\[\"([^\"]*)\"\]'''			,       A		)		)		)

			UpperCAmelCase_      :       Union[str, Any]          =       [
			    module
			    for module in get_transformers_submodules()
			    if module not in IGNORE_SUBMODULES and module not in import_structure_keys
			]

			if len(A		) > 0:
						UpperCAmelCase_      :       Optional[Any]          =       '''\n'''.join(F"- {module}" for module in module_not_registered		)
						raise ValueError(
						    '''The following submodules are not properly registed in the main init of Transformers:\n'''
						    F"{list_of_modules}\n"
						    '''Make sure they appear somewhere in the keys of `_import_structure` with an empty list as value.'''		)


if __name__ == "__main__":
						check_all_inits()
						check_submodules()










'''simple docstring'''





import argparse
import collections
import json
import os
import re
import string
import sys

import numpy as np


_UpperCamelCase						:						List[str]  =					re.compile(R'\b(a|an|the)\b', re.UNICODE)

_UpperCamelCase						:						Optional[int]  =					None
def __UpperCAmelCase   (					)    ->   Optional[Any]:
			UpperCAmelCase_      :       List[Any]          =       argparse.ArgumentParser('''Official evaluation script for SQuAD version 2.0.'''		)
			parser.add_argument('''data_file'''			,       metavar='''data.json'''			,       help='''Input data JSON file.'''		)
			parser.add_argument('''pred_file'''			,       metavar='''pred.json'''			,       help='''Model predictions.'''		)
			parser.add_argument(
			    '''--out-file'''			,       '''-o'''			,       metavar='''eval.json'''			,       help='''Write accuracy metrics to file (default is stdout).'''		)
			parser.add_argument(
			    '''--na-prob-file'''			,       '''-n'''			,       metavar='''na_prob.json'''			,       help='''Model estimates of probability of no answer.'''		)
			parser.add_argument(
			    '''--na-prob-thresh'''			,       '''-t'''			,       type=A			,       default=1.0			,       help='''Predict "" if no-answer probability exceeds this (default = 1.0).'''			,       )
			parser.add_argument(
			    '''--out-image-dir'''			,       '''-p'''			,       metavar='''out_images'''			,       default=A			,       help='''Save precision-recall curves to directory.'''		)
			parser.add_argument('''--verbose'''			,       '''-v'''			,       action='''store_true'''		)
			if len(sys.argv		) == 1:
						parser.print_help()
						sys.exit(1		)
			return parser.parse_args()
def __UpperCAmelCase   (					A					:			int		)    ->   Optional[Any]:
			UpperCAmelCase_      :       Optional[Any]          =       {}
			for article in dataset:
						for p in article["paragraphs"]:
									for qa in p["qas"]:
												UpperCAmelCase_      :       Union[str, Any]          =       bool(qa['''answers''']['''text''']		)
			return qid_to_has_ans
def __UpperCAmelCase   (					A					:			List[Any]		)    ->   Dict:

			def remove_articles(A					:			Dict		):
						return ARTICLES_REGEX.sub(''' '''			,       A		)

			def white_space_fix(A					:			str		):
						return " ".join(text.split()		)

			def remove_punc(A					:			Tuple		):
						UpperCAmelCase_      :       Dict          =       set(string.punctuation		)
						return "".join(ch for ch in text if ch not in exclude		)

			def lower(A					:			Any		):
						return text.lower()

			return white_space_fix(remove_articles(remove_punc(lower(A		)		)		)		)
def __UpperCAmelCase   (					A					:			Optional[Any]		)    ->   Tuple:
			if not s:
						return []
			return normalize_answer(A		).split()
def __UpperCAmelCase   (					A					:			Optional[int]			,       A					:			Dict		)    ->   List[str]:
			return int(normalize_answer(A		) == normalize_answer(A		)		)
def __UpperCAmelCase   (					A					:			Optional[Any]			,       A					:			List[Any]		)    ->   str:
			UpperCAmelCase_      :       Tuple          =       get_tokens(A		)
			UpperCAmelCase_      :       Union[str, Any]          =       get_tokens(A		)
			UpperCAmelCase_      :       Dict          =       collections.Counter(A		) & collections.Counter(A		)
			UpperCAmelCase_      :       Optional[int]          =       sum(common.values()		)
			if len(A		) == 0 or len(A		) == 0:
						# If either is no-answer, then F1 is 1 if they agree, 0 otherwise
						return int(gold_toks == pred_toks		)
			if num_same == 0:
						return 0
			UpperCAmelCase_      :       int          =       1.0 * num_same / len(A		)
			UpperCAmelCase_      :       Any          =       1.0 * num_same / len(A		)
			UpperCAmelCase_      :       Any          =       (2 * precision * recall) / (precision + recall)
			return fa
def __UpperCAmelCase   (					A					:			Union[str, Any]			,       A					:			str		)    ->   Union[str, Any]:
			UpperCAmelCase_      :       List[Any]          =       {}
			UpperCAmelCase_      :       str          =       {}
			for article in dataset:
						for p in article["paragraphs"]:
									for qa in p["qas"]:
												UpperCAmelCase_      :       Optional[Any]          =       qa['''id''']
												UpperCAmelCase_      :       List[str]          =       [t for t in qa['''answers''']['''text'''] if normalize_answer(A		)]
												if not gold_answers:
															# For unanswerable questions, only correct answer is empty string
															UpperCAmelCase_      :       Tuple          =       ['''''']
												if qid not in preds:
															print(F"Missing prediction for {qid}"		)
															continue
												UpperCAmelCase_      :       Tuple          =       preds[qid]
												# Take max over all gold answers
												UpperCAmelCase_      :       List[Any]          =       max(compute_exact(A			,       A		) for a in gold_answers		)
												UpperCAmelCase_      :       int          =       max(compute_fa(A			,       A		) for a in gold_answers		)
			return exact_scores, fa_scores
def __UpperCAmelCase   (					A					:			Optional[int]			,       A					:			Tuple			,       A					:			Optional[Any]			,       A					:			List[Any]		)    ->   Optional[int]:
			UpperCAmelCase_      :       Tuple          =       {}
			for qid, s in scores.items():
						UpperCAmelCase_      :       Union[str, Any]          =       na_probs[qid] > na_prob_thresh
						if pred_na:
									UpperCAmelCase_      :       List[str]          =       float(not qid_to_has_ans[qid]		)
						else:
									UpperCAmelCase_      :       Any          =       s
			return new_scores
def __UpperCAmelCase   (					A					:			Any			,       A					:			Any			,       A					:			str=None		)    ->   int:
			if not qid_list:
						UpperCAmelCase_      :       str          =       len(A		)
						return collections.OrderedDict(
						    [
						        ('''exact''', 100.0 * sum(exact_scores.values()		) / total),
						        ('''f1''', 100.0 * sum(fa_scores.values()		) / total),
						        ('''total''', total),
						    ]		)
			else:
						UpperCAmelCase_      :       Dict          =       len(A		)
						return collections.OrderedDict(
						    [
						        ('''exact''', 100.0 * sum(exact_scores[k] for k in qid_list		) / total),
						        ('''f1''', 100.0 * sum(fa_scores[k] for k in qid_list		) / total),
						        ('''total''', total),
						    ]		)
def __UpperCAmelCase   (					A					:			Union[str, Any]			,       A					:			Dict			,       A					:			Union[str, Any]		)    ->   Dict:
			for k in new_eval:
						UpperCAmelCase_      :       str          =       new_eval[k]
def __UpperCAmelCase   (					A					:			str			,       A					:			Tuple			,       A					:			Any			,       A					:			List[str]		)    ->   Optional[int]:
			plt.step(A			,       A			,       color='''b'''			,       alpha=0.2			,       where='''post'''		)
			plt.fill_between(A			,       A			,       step='''post'''			,       alpha=0.2			,       color='''b'''		)
			plt.xlabel('''Recall'''		)
			plt.ylabel('''Precision'''		)
			plt.xlim([0.0, 1.05]		)
			plt.ylim([0.0, 1.05]		)
			plt.title(A		)
			plt.savefig(A		)
			plt.clf()
def __UpperCAmelCase   (					A					:			Optional[Any]			,       A					:			Optional[Any]			,       A					:			Optional[int]			,       A					:			Optional[int]			,       A					:			str=None			,       A					:			Any=None		)    ->   Any:
			UpperCAmelCase_      :       Optional[Any]          =       sorted(A			,       key=lambda A		: na_probs[k]		)
			UpperCAmelCase_      :       int          =       0.0
			UpperCAmelCase_      :       List[Any]          =       1.0
			UpperCAmelCase_      :       Optional[int]          =       0.0
			UpperCAmelCase_      :       Optional[Any]          =       [1.0]
			UpperCAmelCase_      :       List[Any]          =       [0.0]
			UpperCAmelCase_      :       Dict          =       0.0
			for i, qid in enumerate(A		):
						if qid_to_has_ans[qid]:
									true_pos += scores[qid]
						UpperCAmelCase_      :       List[Any]          =       true_pos / float(i + 1		)
						UpperCAmelCase_      :       Union[str, Any]          =       true_pos / float(A		)
						if i == len(A		) - 1 or na_probs[qid] != na_probs[qid_list[i + 1]]:
									# i.e., if we can put a threshold after this point
									avg_prec += cur_p * (cur_r - recalls[-1])
									precisions.append(A		)
									recalls.append(A		)
			if out_image:
						plot_pr_curve(A			,       A			,       A			,       A		)
			return {"ap": 100.0 * avg_prec}
def __UpperCAmelCase   (					A					:			List[Any]			,       A					:			str			,       A					:			Any			,       A					:			Optional[int]			,       A					:			Any			,       A					:			List[str]		)    ->   List[Any]:
			if out_image_dir and not os.path.exists(A		):
						os.makedirs(A		)
			UpperCAmelCase_      :       Any          =       sum(1 for v in qid_to_has_ans.values() if v		)
			if num_true_pos == 0:
						return
			UpperCAmelCase_      :       Union[str, Any]          =       make_precision_recall_eval(
			    A			,       A			,       A			,       A			,       out_image=os.path.join(A			,       '''pr_exact.png'''		)			,       title='''Precision-Recall curve for Exact Match score'''			,       )
			UpperCAmelCase_      :       List[str]          =       make_precision_recall_eval(
			    A			,       A			,       A			,       A			,       out_image=os.path.join(A			,       '''pr_f1.png'''		)			,       title='''Precision-Recall curve for F1 score'''			,       )
			UpperCAmelCase_      :       Dict          =       {k: float(A		) for k, v in qid_to_has_ans.items()}
			UpperCAmelCase_      :       Optional[int]          =       make_precision_recall_eval(
			    A			,       A			,       A			,       A			,       out_image=os.path.join(A			,       '''pr_oracle.png'''		)			,       title='''Oracle Precision-Recall curve (binary task of HasAns vs. NoAns)'''			,       )
			merge_eval(A			,       A			,       '''pr_exact'''		)
			merge_eval(A			,       A			,       '''pr_f1'''		)
			merge_eval(A			,       A			,       '''pr_oracle'''		)
def __UpperCAmelCase   (					A					:			List[str]			,       A					:			Tuple			,       A					:			str			,       A					:			List[Any]		)    ->   Dict:
			if not qid_list:
						return
			UpperCAmelCase_      :       List[Any]          =       [na_probs[k] for k in qid_list]
			UpperCAmelCase_      :       Union[str, Any]          =       np.ones_like(A		) / float(len(A		)		)
			plt.hist(A			,       weights=A			,       bins=2_0			,       range=(0.0, 1.0)		)
			plt.xlabel('''Model probability of no-answer'''		)
			plt.ylabel('''Proportion of dataset'''		)
			plt.title(F"Histogram of no-answer probability: {name}"		)
			plt.savefig(os.path.join(A			,       F"na_prob_hist_{name}.png"		)		)
			plt.clf()
def __UpperCAmelCase   (					A					:			str			,       A					:			Dict			,       A					:			List[str]			,       A					:			int		)    ->   Optional[Any]:
			UpperCAmelCase_      :       Tuple          =       sum(1 for k in qid_to_has_ans if not qid_to_has_ans[k]		)
			UpperCAmelCase_      :       Optional[Any]          =       num_no_ans
			UpperCAmelCase_      :       int          =       cur_score
			UpperCAmelCase_      :       List[Any]          =       0.0
			UpperCAmelCase_      :       Dict          =       sorted(A			,       key=lambda A		: na_probs[k]		)
			for i, qid in enumerate(A		):
						if qid not in scores:
									continue
						if qid_to_has_ans[qid]:
									UpperCAmelCase_      :       Tuple          =       scores[qid]
						else:
									if preds[qid]:
												UpperCAmelCase_      :       Optional[int]          =       -1
									else:
												UpperCAmelCase_      :       int          =       0
						cur_score += diff
						if cur_score > best_score:
									UpperCAmelCase_      :       Dict          =       cur_score
									UpperCAmelCase_      :       Dict          =       na_probs[qid]
			return 100.0 * best_score / len(A		), best_thresh
def __UpperCAmelCase   (					A					:			int			,       A					:			List[Any]			,       A					:			Union[str, Any]			,       A					:			Tuple			,       A					:			str			,       A					:			Union[str, Any]		)    ->   Tuple:
			UpperCAmelCase_    ,      UpperCAmelCase_      :       List[Any]          =       find_best_thresh(A			,       A			,       A			,       A		)
			UpperCAmelCase_    ,      UpperCAmelCase_      :       Optional[int]          =       find_best_thresh(A			,       A			,       A			,       A		)
			UpperCAmelCase_      :       List[str]          =       best_exact
			UpperCAmelCase_      :       List[Any]          =       exact_thresh
			UpperCAmelCase_      :       Any          =       best_fa
			UpperCAmelCase_      :       str          =       fa_thresh
def __UpperCAmelCase   (					)    ->   Tuple:
			with open(OPTS.data_file		) as f:
						UpperCAmelCase_      :       Optional[int]          =       json.load(A		)
						UpperCAmelCase_      :       str          =       dataset_json['''data''']
			with open(OPTS.pred_file		) as f:
						UpperCAmelCase_      :       List[Any]          =       json.load(A		)
			if OPTS.na_prob_file:
						with open(OPTS.na_prob_file		) as f:
									UpperCAmelCase_      :       List[str]          =       json.load(A		)
			else:
						UpperCAmelCase_      :       List[str]          =       {k: 0.0 for k in preds}
			UpperCAmelCase_      :       Optional[Any]          =       make_qid_to_has_ans(A		)  # maps qid to True/False
			UpperCAmelCase_      :       Optional[int]          =       [k for k, v in qid_to_has_ans.items() if v]
			UpperCAmelCase_      :       Dict          =       [k for k, v in qid_to_has_ans.items() if not v]
			UpperCAmelCase_    ,      UpperCAmelCase_      :       List[Any]          =       get_raw_scores(A			,       A		)
			UpperCAmelCase_      :       Optional[int]          =       apply_no_ans_threshold(A			,       A			,       A			,       OPTS.na_prob_thresh		)
			UpperCAmelCase_      :       Tuple          =       apply_no_ans_threshold(A			,       A			,       A			,       OPTS.na_prob_thresh		)
			UpperCAmelCase_      :       int          =       make_eval_dict(A			,       A		)
			if has_ans_qids:
						UpperCAmelCase_      :       Optional[int]          =       make_eval_dict(A			,       A			,       qid_list=A		)
						merge_eval(A			,       A			,       '''HasAns'''		)
			if no_ans_qids:
						UpperCAmelCase_      :       Dict          =       make_eval_dict(A			,       A			,       qid_list=A		)
						merge_eval(A			,       A			,       '''NoAns'''		)
			if OPTS.na_prob_file:
						find_all_best_thresh(A			,       A			,       A			,       A			,       A			,       A		)
			if OPTS.na_prob_file and OPTS.out_image_dir:
						run_precision_recall_analysis(A			,       A			,       A			,       A			,       A			,       OPTS.out_image_dir		)
						histogram_na_prob(A			,       A			,       OPTS.out_image_dir			,       '''hasAns'''		)
						histogram_na_prob(A			,       A			,       OPTS.out_image_dir			,       '''noAns'''		)
			if OPTS.out_file:
						with open(OPTS.out_file			,       '''w'''		) as f:
									json.dump(A			,       A		)
			else:
						print(json.dumps(A			,       indent=2		)		)


if __name__ == "__main__":
						_UpperCamelCase						:						Union[str, Any]  =					parse_args()
						if OPTS.out_image_dir:
												import matplotlib

												matplotlib.use('Agg')
												import matplotlib.pyplot as plt
						main()


